Rapid high-resolution magnetic field measurements for power line inspection

ABSTRACT

Methods and configurations are disclosed for DNV application in rapid and cost-effective inspection of power transmission and power distribution lines.

The present application claims the benefit of U.S. Provisional Application Nos. 62/109,006, filed Jan. 28, 2015, and 62/109,551, filed Jan. 29, 2015, each of which is incorporated by reference herein in its entirety. The present application is related to co-pending U.S. Application No. __/___,___, filed Jan. 21, 2016, titled “MAGNETIC NAVIGATION METHODS AND SYSTEMS UTILIZING POWER GRID AND COMMUNICATION NETWORK,” which is incorporated by reference herein in its entirety. The present application is also related to co-pending U.S. Application No. __/___,___, filed Jan. 21, 2016, titled “IN-SITU POWER CHARGING”, which is incorporated by reference herein in its entirety.

FIELD

The disclosure generally relates to magnetometer systems, and more particularly, to diamond nitrogen-vacancy (DNV) magnetometer systems to inspection of human infrastructure such as power lines and cellular communications networks.

BACKGROUND

Transmission lines, such as power lines, can acquire defects over time and use. These defects can adversely affect transmission of current and ultimately lead to failure of the transmission line. Current methods of inspecting transmission lines include manually inspecting transmission lines. For example, a helicopter can be used to position the inspector close enough to visually inspect transmission lines. Given the safety considerations of such an inspection, the inspector is not able to get extremely close to the power lines and thus, the visual inspection is limited.

SUMMARY

Methods and systems are described for exploiting magnetic signature characteristics of electrical power transmission, distribution lines and other magnetic sources for inspection of these items for defects. In the following description, reference is made to the accompanying attachments that form a part thereof, and in which are shown by way of illustration, specific embodiments in which the subject technology may be practiced. It is to be understood that other embodiments may be utilized and changes may be made without departing from the scope of the subject technology. For example, the same principals disclosed apply to ground autonomous vehicles that can follow the same overhead and buried power lines, and to undersea autonomous vehicles that can follow submerged power cables and other infrastructure. In addition, groups of unmanned systems may improve the scope, accuracy and types of features represented in the magnetic database described below. Magnetic metadata for way-point determination and other applications such as homing can be collected at will with the system described. Metadata can be compiled in a central database and/or shared in real-time with other platforms and sensors for navigation and homing. In addition, platforms may coordinate their information other platforms to allow those more distant platforms, with or without a magnetic sensor, to more accurately locate their positions.

BRIEF DESCRIPTION OF THE DRAWINGS

The foregoing and other features of the present disclosure will become more fully apparent from the following description and appended claims, taken in conjunction with the accompanying drawings. Understanding that these drawings depict only several implementations in accordance with the disclosure and are, therefore, not to be considered limiting of its scope, the disclosure will be described with additional specificity and detail through use of the accompanying drawings.

FIG. 1 illustrates a low altitude flying object in accordance with some illustrative implementations.

FIG. 2A illustrates a ratio of signal strength of two magnetic sensors, A and B, attached to wings of the UAS 102 as a function of distance, x, from a center line of a power in accordance with some illustrative implementations.

FIG. 2B illustrates a composite magnetic field (B-field) in accordance with some illustrative implementations.

FIG. 3 illustrates a high-level block diagram of an example UAS navigation system in accordance with some illustrative implementations.

FIG. 4 illustrates an example of a power line infrastructure.

FIGS. 5A and 5B illustrate examples of magnetic field distribution for overhead power lines and underground power cables.

FIG. 6 illustrates examples of magnetic field strength of power lines as a function of distance from the centerline.

FIG. 7 illustrates an example of a UAS equipped with DNV sensors in accordance with some illustrative implementations.

FIG. 8 illustrates a plot of a measured differential magnetic field sensed by the DNV sensors when in close proximity of the power lines in accordance with some illustrative implementations.

FIG. 9 illustrates an example of a measured magnetic field distribution for normal power lines and power lines with anomalies according to some implementations.

FIGS. 10A and 10B are block diagrams of a system for detecting deformities in transmission lines in accordance with an illustrative embodiment

FIG. 11 illustrates current paths through a transmission line with a deformity in accordance with an illustrative embodiment.

FIG. 12 illustrates power transmission line sag between transmission towers in accordance with an illustrative embodiment.

FIG. 13 illustrates vector measurements indicating power transmission line sag in accordance with an illustrative embodiment.

FIG. 14 illustrates vector measurements along a path between adjacent towers in accordance with an illustrative embodiment.

FIG. 15 is a diagram illustrating an example of a system for implementing some aspects of the subject technology in accordance with some implementations.

DETAILED DESCRIPTION

In some aspects of the present technology, methods and configurations are disclosed for diamond nitrogen-vacancy (DNV) application to detection of defects in power transmission or distribution lines. A characteristic magnetic signature of power infrastructure may be used for inspection of the infrastructure. For example, power lines without defects have characteristic magnetic signatures. The magnetic signature of a power line can be measured and compared to the expected magnetic signature. Measured differences can indicate that there is a defect in the transmission line.

In some implementations, a magnetic sensor may be used to measure the magnetic signature of a transmission line. For example, the magnetic sensor can be equipped on a manned vehicle. The manned vehicle can move along the transmission line to measure the magnetic signature of the transmission line. In other implementations, the magnetic sensor can be included in an unmanned vehicle. The transmission line can then also be used to navigate the unmanned vehicle, allowing for unmanned inspection of the transmission line. An unmanned vehicle can maneuver using power lines and can also inspect the same power lines for defects.

Because the magnetic fields are being measured, the measurements of these magnetic fields are not hindered by vegetation or poor visibility conditions that impact other inspection methods such as a visual, optical, and laser inspection methods. Accordingly, the detection of defects such as a downed power line can proceed in poor visibility weather or when vegetation has overgrown the power lines.

In some implementations, the subject technology can include one or more magnetic sensors, a magnetic navigation database, and a feedback loop that can control an unmanned vehicle's position and orientation. High sensitivity to magnetic fields of DNV magnetic sensors for magnetic field measurements can be utilized. The DNV magnetic sensor can also be low cost, space, weight, and power (C-SWAP) and benefit from a fast settling time. The DNV magnetic field measurements allow UAS systems to align themselves with the power lines, and to rapidly move along the power-line infrastructure routes. Navigation is enabled in poor visibility conditions and/or in GPS-denied environments. Further, the UAS operation may occur in close proximity to power lines facilitating stealthy transit. DNV-based magnetic sensors can be approximately 100 times smaller than conventional magnetic sensors and can have a reaction time that that is approximately 100,000 times faster than sensors with similar sensitivity.

FIG. 1 is a conceptual diagram illustrating an example of an UAS 102 navigation along power lines 104, 106, and 108, according to some implementations of the subject technology. The UAS 102 can exploit the distinct magnetic signatures of power lines for navigation such that the power lines can serve as roads and highways for the UAS 102 without the need for detailed a priori knowledge of the route magnetic characteristics. As shown in FIG. 2A, a ratio of signal strength of two magnetic sensors, A and B (110 and 112 in FIG. 1), attached to wings of the UAS 102, varies as a function of distance, x, from a center line of an example three-line power transmission line structure 104, 106, and 108. When the ratio is near 1, point 222, the UAS 102 is centered over the power transmission line structure, x=0 at point 220.

A composite magnetic field (B-field) 206 from all (3) wires shown in FIG. 2B. This field is an illustration of the strength of the magnetic field measured by one or more magnetic sensors in the UAS. In this example, the peak of the field 208 corresponds to the UAS 102 being above the location of the middle line 106. When the UAS 102 has two magnetic sensors, the sensors would read strengths corresponding to points 202 and 204. A computing system on the UAS or remote from the UAS, can calculate combined readings. Not all of the depicted components may be required, however, and one or more implementations may include additional components not shown in the figure. Variations in the arrangement and type of the components may be made, and additional components, different components, or fewer components may be provided.

As an example of various implementations, a vehicle, such as a UAS, can include one or more navigation sensors, such as DNV sensors. The vehicle's goal could be to travel to an initial destination and possibly return to a final destination. Known navigation systems can be used to navigate the vehicle to an intermediate location. For example, a UAS can fly using GPS and/or human controlled navigation to the intermediate location. The UAS can then begin looking for the magnetic signature of a power source, such as power lines. To find a power line, the UAS can continually take measurements using the DNV sensors. The UAS can fly in a circle, straight line, curved pattern, etc. and monitor the recorded magnetic field. The magnetic field can be compared to known characteristics of power lines to identify if a power line is in the vicinity of the UAS. For example, the measured magnetic field can be compared with known magnetic field characteristics of power lines to identify the power line that is generating the measured magnetic field. In addition, information regarding the electrical infrastructure can be used in combination with the measured magnetic field to identify the current source. For example, a database regarding magnetic measurements from the area that were previously taken and recorded can be used to compare the current readings to help determine the UAS's location.

In various implementations, once the UAS identifies a power line the UAS positions itself at a known elevation and position relative to the power line. For example, as the UAS flies over a power line, the magnetic field will reach a maximum value and then begin to decrease as the UAS moves away from the power line. After one sweep of a known distance, the UAS can return to where the magnetic field was the strongest. Based upon known characteristics of power lines and the magnetic readings, the UAS can determine the type of power line.

Once the current source has been identified, the UAS can change its elevation until the magnetic field is a known value that corresponds with an elevation above the identified power line. For example, as shown in FIG. 6, a magnetic field strength can be used to determine an elevation above the current source. The UAS can also use the measured magnetic field to position itself offset from directly above the power line. For example, once the UAS is positioned above the current source, the UAS can move laterally to an offset position from the current source. For example, the UAS can move to be 10 kilometers to the left or right of the current source.

The UAS can be programmed, via a computer 306, with a flight path. In various implementations, once the UAS establishes its position, the UAS can use a flight path to reach its destination. In various implementations, the magnetic field generated by the transmission line is perpendicular to the transmission line. In these implementations, the vehicle will fly perpendicular to the detected magnetic field. In one example, the UAS can follow the detected power line to its destination. In this example, the UAS will attempt to keep the detected magnetic field to be close to the original magnetic field value. To do this, the UAS can change elevation or move laterally to stay in its position relative to the power line. For example, a power line that is rising in elevation would cause the detected magnetic field to increase in strength as the distance between the UAS and power line decreased. The navigation system of the UAS can detect this increased magnetic strength and increase the elevation of the UAS. In addition, on board instruments can provide an indication of the elevation of the UAS. The navigation system can also move the UAS laterally to the keep the UAS in the proper position relative to the power lines.

The magnetic field can become weaker or stronger, as the UAS drifts from its position of the transmission line. As the change in the magnetic field is detected, the navigation system can make the appropriate correction. For a UAS that only has a single DNV sensor, when the magnetic field had decreased by more than a predetermined amount the navigation system can make corrections. For example, the UAS can have an error budget such that the UAS will attempt to correct its course if the measured error is greater than the error budget. If the magnetic field has decreased, the navigation system can instruct the UAS to move to the left. The navigation system can continually monitor the magnetic field to see if moving to the left corrected the error. If the magnetic field further decreased, the navigation system can instruct the UAS to fly to the right to its original position relative to the current source and then move further to the right. If the magnetic field decreased in strength, the navigation system can deduce that the UAS needs to decrease its altitude to increase the magnetic field. In this example, the UAS would originally be flying directly over the current source, but the distance between the current source and the UAS has increased due to the current source being at a lower elevation. Using this feedback loop of the magnetic field, the navigation system can keep the UAS centered or at an offset of the current source. The same analysis can be done when the magnetic field increases in strength. The navigation can maneuver until the measured magnetic field is within the proper range such that the UAS in within the flight path.

The UAS can also use the vector measurements from one or more DNV sensors to determine course corrections. The readings from the DNV sensor are vectors that indicate the direction of the sensed magnetic field. Once the UAS knows the location of the power line, as the magnitude of the sensed magnetic field decreases, the vector can provide an indication of the direction the UAS should move to correct its course. For example, the strength of the magnetic field can be reduced by a threshold amount from its ideal location. The magnetic vector of this field can be used to indicate the direction the UAS should correct to increase the strength of the magnetic field. In other words, the magnetic field indicates the direction of the field and the UAS can use this direction to determine the correct direction needed to increase the strength of the magnetic field, which could correct the UAS flight path to be back over the transmission wire.

Using multiple sensors on a single vehicle can reduce the amount of maneuvering that is needed or eliminate the maneuvering all together. Using the measured magnetic field from each of the multiple sensors, the navigation system can determine if the UAS needs to correct its course by moving left, right, up, or down. For example, if both DNV sensors are reading a stronger field, the navigation system can direct the UAS to increase its altitude. As another example if the left sensor is stronger than expected but the right sensor is weaker than expected, the navigation system can move the UAS to the left.

In addition to the current readings from the one or more sensors, a recent history of readings can also be used by the navigation system to identify how to correct the UAS course. For example, if the right sensor had a brief increase in strength and then a decrease, while the left sensor had a decrease, the navigation system can determine that the UAS has moved to far to the left of the flight path and could correct the position of the UAS accordingly.

FIG. 3 illustrates a high-level block diagram of an example UAS navigation system 300, according to some implementations of the subject technology. In some implementations, the UAS navigation system of the subject technology includes a number of DNV sensors 302 a, 302 b, and 302 c, a navigation database 304, and a feedback loop that controls the UAS position and orientation. In other implementations, a vehicle can contain a navigation control that is used to navigate the vehicle. For example, the navigation control can change the vehicle's direction, elevation, speed, etc. The DNV magnetic sensors 302 a-302 c have high sensitivity to magnetic fields, low C-SWAP and a fast settling time. The DNV magnetic field measurements allow the UAS to align itself with the power lines, via its characteristic magnetic field signature, and to rapidly move along power-line routes. Not all of the depicted components may be required, however, and one or more implementations may include additional components not shown in the figure. Variations in the arrangement and type of the components may be made, and additional components, different components, or fewer components may be provided.

FIG. 4 illustrates an example of a power line infrastructure. It is known that widespread power line infrastructures, such as shown in FIG. 4, connect cities, critical power system elements, homes and businesses. The infrastructure may include overhead and buried power distribution lines, transmission lines, railway catenary and 3^(rd) rail power lines and underwater cables. Each element has a unique electro-magnetic and spatial signature. It is understood that, unlike electric fields, the magnetic signature is minimally impacted by man-made structures and electrical shielding. It is understood that specific elements of the infrastructure will have distinct magnetic and spatial signatures and that discontinuities, cable droop, power consumption and other factors will create variations in magnetic signatures that can also be leveraged for navigation.

FIGS. 5A and 5B illustrate examples of magnetic field distribution for overhead power lines and underground power cables. Both above-ground and buried power cables emit magnetic fields, which unlike electrical fields are not easily blocked or shielded. Natural Earth and other man-made magnetic field sources can provide rough values of absolute location. However, the sensitive magnetic sensors described here can locate strong man-made magnetic sources, such as power lines, at substantial distances. As the UAS moves, the measurements can be used to reveal the spatial structure of the magnetic source (point source, line source, etc.) and thus identify the power line as such. In addition, once detected the UAS can guide itself to the power line via its magnetic strength. Once the power line is located its structure is determined, and the power line route is followed and its characteristics are compared to magnetic way points to determine absolute location. Fixed power lines can provide precision location reference as the location and relative position of poles and towers are known. A compact on-board database can provide reference signatures and location data for waypoints. Not all of the depicted components may be required, however, and one or more implementations may include additional components not shown in the figure. Variations in the arrangement and type of the components may be made, and additional components, different components, or fewer components may be provided.

FIG. 6 illustrates examples of magnetic field strength of power lines as a function of distance from the centerline showing that even low current distribution lines can be detected to distances in excess of 10 km. Here it is understood that DNV sensors provide 0.01 uT sensitivity (1e-10 T), and modeling results indicates that high current transmission line (e.g. with 1000 A-4000 A) can be detected over many tens of km. These strong magnetic sources allow the UAS to guide itself to the power lines where it can then align itself using localized relative field strength and the characteristic patterns of the power-line configuration as described below.

FIG. 7 illustrates an example of a UAS 702 equipped with DNV sensors 704 and 706. FIG. 8 is a plot of a measured differential magnetic field sensed by the DNV sensors when in close proximity of the power lines. While power line detection can be performed with only a single DNV sensor precision alignment for complex wire configurations can be achieved using multiple arrayed sensors. For example, the differential signal can eliminate the influence of diurnal and seasonal variations in field strength. Not all of the depicted components may be required, however, and one or more implementations may include additional components not shown in the figure. Variations in the arrangement and type of the components may be made, and additional components, different components, or fewer components may be provided.

In various other implementations, a vehicle can also be used to inspect power transmission lines, power lines, and power utility equipment. For example, a vehicle can include one or more magnetic sensors, a magnetic waypoint database, and an interface to UAS flight control. The subject technology may leverage high sensitivity to magnetic fields of DNV magnetic sensors for magnetic field measurements. The DNV magnetic sensor can also be low cost, space, weight, and power (C-SWAP) and benefit from a fast settling time. The DNV magnetic field measurements allow UASs to align themselves with the power lines, and to rapidly move along power-line routes and navigate in poor visibility conditions and/or in GPS-denied environments. It is understood that DNV-based magnetic sensors are approximately 100 times smaller than conventional magnetic sensors and have a reaction time that that is approximately 100,000 times faster than sensors with similar sensitivity such as the EMDEX LLC Snap handheld magnetic field survey meter.

The fast settling time and low C-SWAP of the DNV sensor enables rapid measurement of detailed power line characteristics from low-C-SWAP UAS systems. In one or more implementations, power lines can be efficiently surveyed via small unmanned aerial vehicles (UAVs) on a routine basis over long distance, which can identify emerging problems and issues through automated field anomaly identification. In other implementations, a land based vehicle or submersible can be used to inspect power lines. Human inspectors are not required to perform the initial inspections. The inspections of the subject technology are quantitative, and thus are not subject to human interpretation as remote video solutions may be.

FIG. 9 illustrates an example of a measured magnetic field distribution for normal power lines 904 and power lines with anomalies 902 according to some implementations. The peak value of the measured magnetic field distribution, for the normal power lines, is in the vicinity of the centerline (e.g., d=0). The inspection method of the subject technology is a high-speed anomaly mapping technique that can be employed for single and multi-wire transmission systems. The subject solution can take advantage of existing software modeling tools for analyzing the inspection data. In one or more implementations, the data of a normal set of power lines may be used as a comparison reference for data resulting from inspection of other power lines (e.g., with anomalies or defects). Damage to wires and support structure alters the nominal magnetic field characteristics and is detected by comparison with nominal magnetic field characteristics of the normal set of power lines. It is understood that the magnetic field measurement is minimally impacted by other structures such as buildings, trees, and the like. Accordingly, the measured magnetic field can be compared to the data from the normal set of power lines and the measured magnetic field's magnitude and if different by a predetermined threshold the existence of the anomaly can be indicated. In addition, the vector reading between the difference data can also be compared and used to determine the existence of anomaly.

FIGS. 10A and 10B are block diagrams of a system for detecting deformities in a transmission line in accordance with an illustrative embodiment. An illustrative system 100 includes a transmission line 1005 and a magnetometer 1030. The magnetometer can be included within a vehicle.

Current flows through the transmission line 1005 as indicated by the arrow labeled 1020. FIGS. 10A and 10B illustrate the direction of a current through the transmission line 1005. As the current 1020 passes through the transmission line 1005 a magnetic field is generated 1025. The magnetometer 1030 can be passed along the length of the transmission line 1005. FIGS. 10A and 10B include an arrow parallel to the length of the transmission line 1005 indicating the relative path of the magnetometer 1030. In alternative embodiments, any suitable path may be used. For example, in some embodiments in which the transmission line 1005 is curved, the magnetometer 1030 can follow the curvature of the transmission line 1005. In addition, the magnetometer 1030 does not have to remain at a constant distance from the transmission line 1005.

The magnetometer 1030 can measure the magnitude and/or direction of the magnetic field along the length of the transmission line 1005. For example, the magnetometer 1030 measures the magnitude and the direction of the magnetic field at multiple sample points along the length of the transmission line 1005 at the same orientation to the transmission line 1005 at the sample points. For instance, the magnetometer 1030 can pass along the length of the transmission line 1005 while above the transmission line 1005.

Any suitable magnetometer can be used as the magnetometer 1030. In some embodiments, the magnetometer uses one or more diamonds with NV centers. The magnetometer 1030 can have a sensitivity suitable for detecting changes in the magnetic field around the transmission line 1005 caused by deformities. In some instances, a relatively insensitive magnetometer 1030 may be used. In such instances, the magnetic field surrounding the transmission line 1005 should be relatively strong. For example, the magnetometer 1030 can have a sensitivity of about 10⁻⁹ Tesla (one nano-Tesla). Transmission lines can carry a large current, which allows detection of the magnetic field generated from the transmission line over a large distances. For example, for high current transmission lines, the magnetometer 1030 can be 10 kilometers away from the transmission source. The magnetometer 1030 can have any suitable measurement rate. For example, the magnetometer 1030 can measure the magnitude and/or the direction of a magnetic field at a particular point in space ten thousand times per second. In another example, the magnetometer 1030 can take a measurement fifty thousand times per second. Further description of operation of a DNV sensor is described in U.S. Patent Application No. __/___,___, entitled “Apparatus and Method for Hypersensitivity Detection of Magnetic Field,” filed on the same day as this application, the contents of which are hereby incorporated by reference.

In some embodiments in which the magnetometer 1030 measures the direction of the magnetic field, the orientation of the magnetometer 1030 to the transmission line 1005 can be maintained along the length of the transmission line 1005. As the magnetometer 1030 passes along the length of the transmission line 1005, the direction of the magnetic field can be monitored. If the direction of the magnetic field changes or is different than an expected value, it can be determined that a deformity exits in the transmission line 1005.

In some embodiments, the magnetometer 1030 can be maintained at the same orientation to the transmission line 1005 because even if the magnetic field around the transmission line 1005 is uniform along the length of the transmission line 1005, the direction of the magnetic field is different at different points around the transmission line 1005. For example, referring to the magnetic field direction 1025 of FIG. 10A, the direction of the magnetic field above the transmission line 1005 is pointing to the right of the transmission line 1005 (e.g., according to the “right-hand rule”). A vehicle carrying the magnetometer would know the magnetometer's relative position to the transmission line 1005. For example, an aerial vehicle would know it's relative position would be above or a known distance offset from the transmission line 1005, while a ground based vehicle would now it's relative position to be below or a known offset from the transmission line 1005. Based upon the relative position of the magnetometer to the transmission line 1005, the direction magnetic vector can be monitored for indicating defects in the transmission line 1005.

In some embodiments in which the magnetometer 1030 measures magnitude of the magnetic field and not the direction of the magnetic field, the magnetometer 1030 can be located at any suitable location around the transmission line 1005 along the length of the transmission line 1005 and the magnetometer 1030 may not be held at the same orientation along the length of the transmission line 1005. In such embodiments, the magnetometer 1030 may be maintained at the same distance from the transmission line 1005 along the length of the transmission line 1005 (e.g., assuming the same material such as air is between the magnetometer 1030 and the transmission line 1005 along the length of the transmission line 1005).

FIG. 10A illustrates the system in which the transmission line 1005 does not contain a deformity. FIG. 10B illustrates in which the transmission line 1005 includes a defect 1035. The defect 1035 can be a crack in the transmission line, a break in the transmission line, a deteriorating portion of the transmission line, etc. A defect 1035 is a condition of the transmission line that affects the current flow through a defect free transmission line. As shown in FIG. 10B, a portion of the current 1020 is reflected back from the defect 1035 as shown by the reflected current 1040. As in FIG. 10B, the magnetic field direction 1025 corresponds to the current 1020. The reflected current magnetic field direction 1045 corresponds to the reflected current 1040. The magnetic field direction 1025 is opposite the reflected current magnetic field direction 1045 because the current 1020 travels in the opposite direction from the reflected current 1040. Accordingly, the magnetic field measured in the transmission line would be based upon both the current 1020 and the reflected current 1040. This magnetic field is different in magnitude and possibly direction from the magnetic field 1025. The difference between the magnetic fields 1020 and 1040 can be calculated and used to indicate the presence of the defect 1035. In some instances, as the magnetometer 1030 travels closer to the defect 1035, the magnitude of the detected magnetic field reduces. In some embodiments, it can be determined that the defect 1035 exists when the measured magnetic field is below a threshold value. In some embodiments, the threshold value may be a percentage of the expected value, such as ±5%, ±10%, ±15%, ±50%, or any other suitable portion of the expected value. In alternative embodiments, any suitable threshold value may be used.

In some embodiments in which the defect 1035 is a full break that breaks conductivity between the portions of the transmission line 1005, the magnitude of the current 1020 may be equal to or substantially similar to reflected current 1040. Thus, the combined magnetic field around the transmission line 1005 will be zero or substantially zero. That is, the magnetic field generated by the current 1020 is canceled out by the equal but opposite magnetic field generated by the reflected current 1040. In such embodiments, the defect 1035 may be detected using the magnetometer 1030 by comparing the measured magnetic field, which is substantially zero, to an expected magnetic field, which is a non-zero amount.

In some embodiments in which the defect 1035 allows some of the current 1020 to pass through or around the defect 1035, the magnitude of the reflected current 1040 is less than the magnitude of the current 1020. Accordingly, the magnitude of the magnetic field generated by the reflected current 1040 is less than the magnitude of the magnetic field generated by the current 1020. Although the magnitudes of the current 1020 and the reflected current 1040 may not be equal, the current magnetic field direction 1025 and the reflected current magnetic field direction 1045 are still opposite. Thus, the net magnetic field will be a magnetic field in the current magnetic field direction 1025. The magnitude of the net magnetic field is the magnitude of the magnetic field generated by the current 1020 reduced based upon the magnitude of the magnetic field generated by the reflected current 1040. As mentioned above, the magnetic field measured by the magnetometer 1030 can be compared against a threshold. Depending upon the severity, size, and/or shape of the defect 1035, the net magnetic field sensed by the magnetometer 1030 may or may not be less than (or greater than) the threshold value. Thus, the threshold value can be adjusted to adjust the sensitivity of the system. That is, the more that the threshold value deviates from the expected value, the larger the deformity in the transmission line 1005 is to cause the magnitude of the sensed magnetic field to be less than the threshold value. Thus, the closer that the threshold value is to the expected value, the finer, smaller, less severe, etc. deformities are detected by the system 100.

As mentioned above, the direction of the magnetic field around the transmission line 1005 can be used to sense a deformity in the transmission line 1005. FIG. 11 illustrates current paths through a transmission line with a deformity 1135 in accordance with an illustrative embodiment. FIG. 11 is meant to be illustrative and explanatory only and not meant to be limiting with respect to the functioning of the system.

A current can be passed through the transmission line 1105, as discussed above. The current paths 1120 illustrate the direction of the current. As shown in FIG. 11, the transmission line 1105 includes a deformity 1135. The deformity 1135 can be any suitable deformity, such as a crack, a dent, an impurity, etc. The current passing through the transmission line 1105 spreads uniformly around the transmission line 1105 in portions that do not include the deformity 1135. In some instances, the current may be more concentrated at the surface of the transmission line 1105 than at the center of the transmission line 1105.

In some embodiments, the deformity 1135 is a portion of the transmission line 1105 that does not allow or resists the flow of electrical current. Thus, the current passing through the transmission line 1105 flows around the deformity 1135. As shown in FIG. 10A, the current magnetic field direction 1025 is perpendicular to the direction of the current 1020. Thus, as in FIG. 10A, when the transmission line 1005 does not include a deformity, the direction of the magnetic field around the transmission line 1005 is perpendicular to the length of the transmission line 1005 all along the length of the transmission line 1005.

As shown in FIG. 11, when the transmission line 1105 includes a deformity 1135 around which the current flows, the direction of the current changes, as shown by the current paths 1120. Thus, even though the transmission line 1105 is straight, the current flowing around the deformity 1135 is not parallel to the length of the transmission line 1105. Accordingly, the magnetic field generated by the current paths corresponding to the curved current paths 1120 is not perpendicular to the length of the transmission line 1105. Thus, as a magnetometer such as the magnetometer 1030 passes along the length of the transmission line 1105, a change in direction of the magnetic field around the transmission line 1105 can indicate that the deformity 1135 exits. As the magnetometer 1030 approaches the deformity 1135, the direction of the magnetic field around the transmission line 1105 changes from being perpendicular to the length of the transmission line 1105. As the magnetometer 1030 passes along the deformity 1135, the change in direction of the magnetic field increases and then decreases as the magnetometer 1030 moves away from the deformity 1135. The change in the direction of the magnetic field can indicate the location of the deformity 1135. In some instances, the transmission line 1105 may have a deformity that reflects a portion of the current, as illustrated in FIG. 10B, and that deflects the flow of the current, as illustrated in FIG. 11.

The size, shape, type, etc. of the deformity 1135 determines the spatial direction of the magnetic field surrounding the deformity 1135. In some embodiments, multiple samples of the magnetic field around the deformity 1135 can be taken to create a map of the magnetic field. In an illustrative embodiment, each of the samples includes a magnitude and direction of the magnetic field. Based on the spatial shape of the magnetic field surrounding the deformity 1135, one or more characteristics of the deformity 1135 can be determined, such as the size, shape, type, etc. of the deformity 1135. For instance, depending upon the map of the magnetic field, it can be determined whether the deformity 1135 is a dent, a crack, an impurity in the transmission line, etc. In some embodiments, the map of the magnetic field surrounding the deformity 1135 can be compared to a database of known deformities. In an illustrative embodiment, it can be determined that the deformity 1135 is similar to or the same as the closest matching deformity from the database. In an alternative embodiment, it can be determined that the deformity 1135 is similar to or the same as a deformity from the database that has a similarity score that is above a threshold score. The similarity score can be any suitable score that measures the similarity between the measured magnetic field and one or more known magnetic fields of the database.

In various implementations, a vehicle that includes one or magnetometers can navigate via the power lines that are being inspected. For example, the vehicle can navigate to an known position, e.g., a starting position, identify the presence of a power line based upon the sensed magnetic vector. Then the vehicle can determine the type of power line and further determine that the type of power line is the type that is to be inspected. The vehicle can then autonomously or semi-autonomously navigate via the power lines as described in detail above, while inspecting the power lines at the same time.

In various implementations, a vehicle may need to avoid objects that are in their navigation path. For example, a ground vehicle may need to maneuver around people or objects, or a flying vehicle may need to avoid a building or power line equipment. In these implementations, the vehicle can be equipment with sensors that are used to locate the obstacles that are to be avoided. Systems such as a camera system, focal point array, radar, acoustic sensors, etc., can be used to identify obstacles in the vehicles path. The navigation system can then identify a course correction to avoid the identified obstacles.

Power transmission lines can be stretched between two transmission towers. In these instances, the power transmission lines can sag between the two transmission towers. The power transmission line sag depends on the weight of the wire, tower spacing and wire tension, which varies with ambient temperature and electrical load. Excessive sagging can cause shorting when the transmission line comes into contact with brush or other surface structures. This can caused power transmission lines to fail.

FIG. 12 illustrates power transmission line sag between transmission towers in accordance with an illustrative embodiment. A transmission line 1210 is shown with “normal” sag 1222. Here sag is determined based upon how far below the transmission line is from the tower height. The transmission line 1210 is stretched between a first tower 1202 and a second tower 1204. A second transmission line 1220 is shown with excessive sag. When this occurs the transmission line 1220 can come into contact with vegetation 1230 or other surface structures that can cause on or failure to the line.

A vector measurement made with a magnetometer mounted on a UAV can measure the wire sag as the UAV flies along the power lines. FIG. 13 depicts the instantaneous measurement of the magnetic field at point X′ as the UAV flies at a fixed height above the towers. A larger horizontal (x) component of the magnetic field indicates more sag. FIG. 14 depicts the variation in magnetic field components for the wire with nominal sag, and for the wire with excessive sag as the UAV transits between towers 1 and 2. The X and Z components for a transmission line under normal/nominal sag are shown (1408 and 1402 respectively). In addition, the X component 1406 and the Z component 1404 of a line experiencing excessive sag is also shown.

The cable sag may be measured by flying the UAV along the cable from tower to tower. FIG. 14 shows the modulation in vector components of the magnetic field for different sag values. A look-up table can be constructed to retrieve the sag from these measurements for wires between each pair of towers along the UAV flight route. Alternatively a database of prior vector measurements can be compared with measurements. In general the flatter the curves the less sag. The exact value of the sag depends on the distance between towers and, which is measured by the UAV, and the angle of the vector at the tower. Combined with weather information and potentially historical data or transmission line sag models, the vector measurements can be used to determine if the power line is experiencing greater or lesser sag as expected. When this occurs, an indication that the power line is experiencing a sag anomaly can be indicated and/or reported.

FIG. 15 is a diagram illustrating an example of a system 1000 for implementing some aspects of the subject technology. The system 1500 includes a processing system 1502, which may include one or more processors or one or more processing systems. A processor can be one or more processors. The processing system 1502 may include a general-purpose processor or a specific-purpose processor for executing instructions and may further include a machine-readable medium 1519, such as a volatile or non-volatile memory, for storing data and/or instructions for software programs. The instructions, which may be stored in a machine-readable medium 1510 and/or 1519, may be executed by the processing system 1502 to control and manage access to the various networks, as well as provide other communication and processing functions. The instructions may also include instructions executed by the processing system 1502 for various user interface devices. The processing system 1502 may include an input port 1522 and an output port 1524. Each of the input port 1522 and the output port 1524 may include one or more ports. The input port 1522 and the output port 1524 may be the same port (e.g., a bi-directional port) or may be different ports.

The processing system 1502 may be implemented using software, hardware, or a combination of both. By way of example, the processing system 1502 may be implemented with one or more processors. A processor may be a general-purpose microprocessor, a microcontroller, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA), a Programmable Logic Device (PLD), a controller, a state machine, gated logic, discrete hardware components, or any other suitable device that can perform calculations or other manipulations of information.

A machine-readable medium can be one or more machine-readable media. Software shall be construed broadly to mean instructions, data, or any combination thereof, whether referred to as software, firmware, middleware, microcode, hardware description language, or otherwise. Instructions may include code (e.g., in source code format, binary code format, executable code format, or any other suitable format of code).

Machine-readable media (e.g., 1519) may include storage integrated into a processing system such as might be the case with an ASIC. Machine-readable media (e.g., 1510) may also include storage external to a processing system, such as a Random Access Memory (RAM), a flash memory, a Read Only Memory (ROM), a Programmable Read-Only Memory (PROM), an Erasable PROM (EPROM), registers, a hard disk, a removable disk, a CD-ROM, a DVD, or any other suitable storage device. Those skilled in the art will recognize how best to implement the described functionality for the processing system 1502. According to one aspect of the disclosure, a machine-readable medium is a computer-readable medium encoded or stored with instructions and is a computing element, which defines structural and functional interrelationships between the instructions and the rest of the system, which permit the instructions' functionality to be realized. Instructions may be executable, for example, by the processing system 1502 or one or more processors. Instructions can be, for example, a computer program including code for performing methods of the subject technology.

A network interface 1516 may be any type of interface to a network (e.g., an Internet network interface), and may reside between any of the components shown in FIG. 15 and coupled to the processor via the bus 1504.

A device interface 1518 may be any type of interface to a device and may reside between any of the components shown in FIG. 15. A device interface 1518 may, for example, be an interface to an external device (e.g., USB device) that plugs into a port (e.g., USB port) of the system 1500.

The foregoing description is provided to enable a person skilled in the art to practice the various configurations described herein. While the subject technology has been particularly described with reference to the various figures and configurations, it should be understood that these are for illustration purposes only and should not be taken as limiting the scope of the subject technology.

One or more of the above-described features and applications may be implemented as software processes that are specified as a set of instructions recorded on a computer readable storage medium (alternatively referred to as computer-readable media, machine-readable media, or machine-readable storage media). When these instructions are executed by one or more processing unit(s) (e.g., one or more processors, cores of processors, or other processing units), they cause the processing unit(s) to perform the actions indicated in the instructions. In one or more implementations, the computer readable media does not include carrier waves and electronic signals passing wirelessly or over wired connections, or any other ephemeral signals. For example, the computer readable media may be entirely restricted to tangible, physical objects that store information in a form that is readable by a computer. In one or more implementations, the computer readable media is non-transitory computer readable media, computer readable storage media, or non-transitory computer readable storage media.

In one or more implementations, a computer program product (also known as a program, software, software application, script, or code) can be written in any form of programming language, including compiled or interpreted languages, declarative or procedural languages, and it can be deployed in any form, including as a stand-alone program or as a module, component, subroutine, object, or other unit suitable for use in a computing environment. A computer program may, but need not, correspond to a file in a file system. A program can be stored in a portion of a file that holds other programs or data (e.g., one or more scripts stored in a markup language document), in a single file dedicated to the program in question, or in multiple coordinated files (e.g., files that store one or more modules, sub programs, or portions of code). A computer program can be deployed to be executed on one computer or on multiple computers that are located at one site or distributed across multiple sites and interconnected by a communication network.

While the above discussion primarily refers to microprocessor or multi-core processors that execute software, one or more implementations are performed by one or more integrated circuits, such as application specific integrated circuits (ASICs) or field programmable gate arrays (FPGAs). In one or more implementations, such integrated circuits execute instructions that are stored on the circuit itself.

In some aspects, the subject technology is directed to DNV application to magnetic navigation via power lines. In some aspects, the subject technology may be used in various markets, including for example and without limitation, advanced sensors and mobile space platforms.

The description of the subject technology is provided to enable any person skilled in the art to practice the various embodiments described herein. While the subject technology has been particularly described with reference to the various figures and embodiments, it should be understood that these are for illustration purposes only and should not be taken as limiting the scope of the subject technology.

There may be many other ways to implement the subject technology. Various functions and elements described herein may be partitioned differently from those shown without departing from the scope of the subject technology. Various modifications to these embodiments may be readily apparent to those skilled in the art, and generic principles defined herein may be applied to other embodiments. Thus, many changes and modifications may be made to the subject technology, by one having ordinary skill in the art, without departing from the scope of the subject technology.

Phrases such as an aspect, the aspect, another aspect, some aspects, one or more aspects, an implementation, the implementation, another implementation, some implementations, one or more implementations, an embodiment, the embodiment, another embodiment, some embodiments, one or more embodiments, a configuration, the configuration, another configuration, some configurations, one or more configurations, the subject technology, the disclosure, the present disclosure, other variations thereof and alike are for convenience and do not imply that a disclosure relating to such phrase(s) is essential to the subject technology or that such disclosure applies to all configurations of the subject technology. A disclosure relating to such phrase(s) may apply to all configurations, or one or more configurations. A disclosure relating to such phrase(s) may provide one or more examples. A phrase such as an aspect or some aspects may refer to one or more aspects and vice versa, and this applies similarly to other foregoing phrases

A reference to an element in the singular is not intended to mean “one and only one” unless specifically stated, but rather “one or more.” The term “some” refers to one or more. Underlined and/or italicized headings and subheadings are used for convenience only, do not limit the subject technology, and are not referred to in connection with the interpretation of the description of the subject technology. All structural and functional equivalents to the elements of the various embodiments described throughout this disclosure that are known or later come to be known to those of ordinary skill in the art are expressly incorporated herein by reference and intended to be encompassed by the subject technology. Moreover, nothing disclosed herein is intended to be dedicated to the public regardless of whether such disclosure is explicitly recited in the above description. 

What is claimed is:
 1. A system for inspecting electric power lines comprising: one or more diamond nitrogen vacancy (DNV) components mounted on a movable object relative to a power line, such DNV components being included as part of a magnetometer configured to detect a magnetic vector of a magnetic field generated as electric power flows along a power line, said magnetometer determining a magnetic vector being generated at intervals along the power line; one or more electronic processors configured to receive the magnetic vector of the magnetic field from the magnetometer, compare the magnetic vector to a predetermined magnetic vector of a power line, and determine a presence of an anomaly related to the power line based upon the comparison.
 2. The system of claim 1, wherein the one or more electronic processors are further configured to determine a presence of the power line based upon the magnetic vector.
 3. The system of claim 2, wherein the one or more electronic processors are further configured to identify a type of power line based upon the magnetic vector.
 4. The system of claim 3, wherein the one or more electronic processors are further configured to determine the predetermined magnetic vector of the power line based upon the type of power line.
 5. The system of claim 4, further comprising a navigation control configured to navigate the vehicle based upon the presence of the power line and the magnetic vector.
 6. The system of claim 5, wherein the navigation control is further configured to navigate to an initial position.
 7. The system of claim 6, wherein the navigation control is further configured to navigate the vehicle in a pattern over an area.
 8. The system of claim 7, wherein the one or more electronic processors are further configured to: receive a plurality of real-time magnetic vectors from the magnetometer; determine a course correction for the vehicle based upon the plurality of magnetic vectors.
 9. The system of claim 8, wherein the course correction follows a curve of the power line.
 10. The system of claim 1, wherein the vehicle is a flying vehicle.
 11. The system of claim 1, wherein the vehicle is a ground vehicle.
 12. The system of claim 1, wherein the vehicle is a submersible vehicle.
 13. The system of claim 1, further comprising a plurality of magnetometers configured to detect a plurality of magnetic vectors of the magnetic field.
 14. The system of claim 13, wherein the one or more processors are further configured to determine a presence of the power line based upon the magnetic vector and the plurality of magnetic vectors.
 15. A method for inspecting power lines comprising: detecting, using a magnetometer, a magnetic vector of a magnetic field; receiving the magnetic vector of the magnetic field from the magnetometer; comparing the magnetic vector to a predetermined magnetic vector of a power line; and determining a presence of an anomaly related to the power line based upon the comparison.
 16. The method of claim 15, further comprising determining a presence of the power line based upon the magnetic vector.
 17. The method of claim 16, further comprising identifying a type of power line based upon the magnetic vector.
 18. The method of claim 17, further comprising determining the predetermined magnetic vector of the power line based upon the type of power line.
 19. The method of claim 18, further comprising navigating, using a navigation control, the vehicle based upon the presence of the power line and the magnetic vector.
 20. The method of claim 19, further comprising navigating, using the navigation control, to an initial position.
 21. The method of claim 20, further comprising navigating, using the navigation control, the vehicle in a pattern over an area.
 22. A method comprising: detecting, using a magnetometer, a magnetic vector of a magnetic field; receiving a plurality of real-time magnetic vectors from the magnetometer; comparing the magnetic vector to a predetermined magnetic vector of a power line; determining a course correction for the vehicle based upon the plurality of magnetic vectors; and determining a presence of an anomaly related to the power line based upon the comparison.
 23. The method of claim 22, wherein the course correction follows a curve of the power line.
 24. The method of claim 15, wherein the vehicle is a flying vehicle.
 25. The method of claim 15, wherein the vehicle is a ground vehicle.
 26. The method of claim 15, wherein the vehicle is a submersible vehicle.
 27. The method of claim 15, further comprising detecting, using a plurality of magnetometers, a plurality of magnetic vectors of the magnetic field.
 28. The method of claim 27, further comprising determining a presence of the power line based upon the magnetic vector and the plurality of magnetic vectors.
 29. A system for inspecting electric power lines comprising: one or more magnetic sensor means mounted on a movable object relative to a power line, the one or more magnetic sensor means configured to detect a magnetic vector of a magnetic field generated as electric power flows along a power line, said magnetic sensor means determining a magnetic vector being generated at intervals along the power line; one or more processor means configured to receive the magnetic vector of the magnetic field from the magnetometer, compare the magnetic vector to a predetermined magnetic vector of a power line, and determine a presence of an anomaly related to the power line based upon the comparison.
 30. A non-transitory computer-readable medium having instructions stored thereon, the instructions comprising: instructions to detect using a magnetometer, a magnetic vector of a magnetic field; instructions to receive the magnetic vector of the magnetic field from the magnetometer; instructions to compare the magnetic vector to a predetermined magnetic vector of a power line; and instructions to determine a presence of an anomaly related to the power line based upon the comparison.
 31. The non-transitory computer-readable medium of claim 30, further comprising instructions to determine a presence of the power line based upon the magnetic vector.
 32. The non-transitory computer-readable medium of claim 31, further comprising instructions to identify a type of power line based upon the magnetic vector.
 33. The non-transitory computer-readable medium of claim 32, further comprising instructions to determine the predetermined magnetic vector of the power line based upon the type of power line.
 34. The non-transitory computer-readable medium of claim 33, further comprising instructions to navigate the vehicle based upon the presence of the power line and the magnetic vector.
 35. The non-transitory computer-readable medium of claim 34, further comprising instructions to navigate to an initial position.
 36. The non-transitory computer-readable medium of claim 35, further comprising instructions to navigate the vehicle in a pattern over an area.
 37. The non-transitory computer-readable medium of claim 36, further comprising: instructions to receive a plurality of real-time magnetic vectors from the magnetometer; instructions to determine a course correction for the vehicle based upon the plurality of magnetic vectors.
 38. The non-transitory computer-readable medium of claim 37, wherein the course correction follows a curve of the power line.
 39. The non-transitory computer-readable medium of claim 30, wherein the vehicle is a flying vehicle.
 40. The non-transitory computer-readable medium of claim 30, wherein the vehicle is a ground vehicle.
 41. The non-transitory computer-readable medium of claim 30, wherein the vehicle is a submersible vehicle.
 42. The non-transitory computer-readable medium of claim 30, further comprising instructions to detect, using a plurality of magnetometers, a plurality of magnetic vectors of the magnetic field.
 43. The non-transitory computer-readable medium of claim 42, further comprising instructions to determine a presence of the power line based upon the magnetic vector and the plurality of magnetic vectors. 